Prostate cancer (PCA) is the most common non-skin cancer and the second leading cause of cancer death in American men, with over 186,000 new cases diagnosed and over 28,000 PCA deaths annually in the United States. Ultrasound-guided biopsy is the standard of care for confirming cancer, typically following elevated PSA levels; however, it has been estimated that up to 20% of men require three or more biopsy sessions for diagnosis, and biopsies have a high risk of hemorrhage and infection. Furthermore, biopsies are not sufficient for tumor delineation or characterization because they sparsely sample the entire organ. Regretfully, the deficiencies of biopsy have lead to over-treatment of indolent disease with radical prostatectomies, a drastic treatment that has significant risks of infection, hemorrhage, urinary incontinence, and impotence. We are the inventors of Acoustic Radiation Force Impulse (ARFI) imaging and the inventors of Shear Wave Elasticity Imaging (SWEI) methods. We have now combined those methods into ARFI-SWEI imaging sequences that define a new and novel multi-parametric ultrasonic elasticity imaging system. This multi-parametric elasticity imaging approach provides an absolute, quantitative measure of tissue stiffness, at high resolution, in 3D, using ultrasound. We hypothesize that synergistic diagnostic information from B-mode, ARFI-SWEI and multi-parametric MRI (mpMRI, e.g., diffusion weighted imaging and MR spectroscopy imaging) enable (a) the sensitive and specific diagnosis of PCA and (b) the accurate delineation of PCA margins. We propose retrospective studies on existing 3D B-mode, ARFI-SWEI and mpMRI imaging datasets to test this hypothesis. 1